Exam 13: Simple Linear Regression

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In a simple linear regression problem, r and b1

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TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, there is sufficient evidence that revenue and the number of downloads are linearly related at a 5% level of significance. TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, there is sufficient evidence that revenue and the number of downloads are linearly related at a 5% level of significance. TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, there is sufficient evidence that revenue and the number of downloads are linearly related at a 5% level of significance. -Referring to Table 13-11, there is sufficient evidence that revenue and the number of downloads are linearly related at a 5% level of significance.

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If the Durbin-Watson statistic has a value close to 0, which assumption is violated?

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TABLE 13-3 The director of cooperative education at a state college wants to examine the effect of cooperative education job experience on marketability in the work place. She takes a random sample of 4 students. For these 4, she finds out how many times each had a cooperative education job and how many job offers they received upon graduation. These data are presented in the table below. TABLE 13-3 The director of cooperative education at a state college wants to examine the effect of cooperative education job experience on marketability in the work place. She takes a random sample of 4 students. For these 4, she finds out how many times each had a cooperative education job and how many job offers they received upon graduation. These data are presented in the table below.    -Referring to Table 13-3, suppose the director of cooperative education wants to construct a 95% confidence interval estimate for the mean number of job offers received by students who have had exactly one cooperative education job. The confidence interval is from ________ to ________. -Referring to Table 13-3, suppose the director of cooperative education wants to construct a 95% confidence interval estimate for the mean number of job offers received by students who have had exactly one cooperative education job. The confidence interval is from ________ to ________.

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TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics    ANOVA        -Referring to Table 13-5, the coefficient of determination is ________. ANOVA TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics    ANOVA        -Referring to Table 13-5, the coefficient of determination is ________. TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics    ANOVA        -Referring to Table 13-5, the coefficient of determination is ________. TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics    ANOVA        -Referring to Table 13-5, the coefficient of determination is ________. -Referring to Table 13-5, the coefficient of determination is ________.

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TABLE 13-10 The management of a chain electronic store would like to develop a model for predicting the weekly sales (in thousands of dollars) for individual stores based on the number of customers who made purchases. A random sample of 12 stores yields the following results: TABLE 13-10 The management of a chain electronic store would like to develop a model for predicting the weekly sales (in thousands of dollars) for individual stores based on the number of customers who made purchases. A random sample of 12 stores yields the following results:    -Referring to Table 13-10, the average weekly sales will increase by an estimated $0.01 for each additional purchasing customer. -Referring to Table 13-10, the average weekly sales will increase by an estimated $0.01 for each additional purchasing customer.

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TABLE 13-3 The director of cooperative education at a state college wants to examine the effect of cooperative education job experience on marketability in the work place. She takes a random sample of 4 students. For these 4, she finds out how many times each had a cooperative education job and how many job offers they received upon graduation. These data are presented in the table below. TABLE 13-3 The director of cooperative education at a state college wants to examine the effect of cooperative education job experience on marketability in the work place. She takes a random sample of 4 students. For these 4, she finds out how many times each had a cooperative education job and how many job offers they received upon graduation. These data are presented in the table below.    -Referring to Table 13-3, suppose the director of cooperative education wants to construct a 95% prediction interval estimate for the number of job offers received by students who have had exactly one cooperative education job. The prediction interval is from ________ to ________. -Referring to Table 13-3, suppose the director of cooperative education wants to construct a 95% prediction interval estimate for the number of job offers received by students who have had exactly one cooperative education job. The prediction interval is from ________ to ________.

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The Chancellor of a university has commissioned a team to collect data on students' GPAs and the amount of time they spend bar hopping every week (measured in minutes). He wants to know if imposing much tougher regulations on all campus bars to make it more difficult for students to spend time in any campus bar will have a significant impact on general students' GPAs. His team should use a t test on the slope of the population regression.

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TABLE 13-8 It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output from regressing GPA on ACT scores using a data set of 8 randomly chosen students from a Big-Ten university. TABLE 13-8 It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output from regressing GPA on ACT scores using a data set of 8 randomly chosen students from a Big-Ten university.    -Referring to Table 13-8, the value of the measured (observed) test statistic of the F-test for H<sub>0</sub> : β<sub>1</sub> = 0 vs. H<sub>1</sub> : β<sub>1</sub> ≠ 0 -Referring to Table 13-8, the value of the measured (observed) test statistic of the F-test for H0 : β1 = 0 vs. H1 : β1 ≠ 0

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TABLE 13-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: TABLE 13-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:    -Referring to Table 13-2, what is the estimated slope parameter for the candy bar price and sales data? -Referring to Table 13-2, what is the estimated slope parameter for the candy bar price and sales data?

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TABLE 13-4 The managers of a brokerage firm are interested in finding out if the number of new clients a broker brings into the firm affects the sales generated by the broker. They sample 12 brokers and determine the number of new clients they have enrolled in the last year and their sales amounts in thousands of dollars. These data are presented in the table that follows. TABLE 13-4 The managers of a brokerage firm are interested in finding out if the number of new clients a broker brings into the firm affects the sales generated by the broker. They sample 12 brokers and determine the number of new clients they have enrolled in the last year and their sales amounts in thousands of dollars. These data are presented in the table that follows.    -Referring to Table 13-4, the standard error of estimate is ________. -Referring to Table 13-4, the standard error of estimate is ________.

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TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics    ANOVA        -Referring to Table 13-5, the value of the quantity that the least squares regression line minimizes is ________. ANOVA TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics    ANOVA        -Referring to Table 13-5, the value of the quantity that the least squares regression line minimizes is ________. TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics    ANOVA        -Referring to Table 13-5, the value of the quantity that the least squares regression line minimizes is ________. TABLE 13-5 The managing partner of an advertising agency believes that his company's sales are related to the industry sales. He uses Microsoft Excel's Data Analysis tool to analyze the last 4 years of quarterly data with the following results: Regression Statistics    ANOVA        -Referring to Table 13-5, the value of the quantity that the least squares regression line minimizes is ________. -Referring to Table 13-5, the value of the quantity that the least squares regression line minimizes is ________.

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TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, what is the p-value for testing whether there is a linear relationship between revenue and the number of downloads at a 5% level of significance? TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, what is the p-value for testing whether there is a linear relationship between revenue and the number of downloads at a 5% level of significance? TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, what is the p-value for testing whether there is a linear relationship between revenue and the number of downloads at a 5% level of significance? -Referring to Table 13-11, what is the p-value for testing whether there is a linear relationship between revenue and the number of downloads at a 5% level of significance?

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TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output: TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output:    Note: 4.3946E-15 is 4.3946×10<sup>-15</sup>      -Referring to Table 13-12, the estimated average amount of time it takes to process one additional invoice is Note: 4.3946E-15 is 4.3946×10-15 TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output:    Note: 4.3946E-15 is 4.3946×10<sup>-15</sup>      -Referring to Table 13-12, the estimated average amount of time it takes to process one additional invoice is TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output:    Note: 4.3946E-15 is 4.3946×10<sup>-15</sup>      -Referring to Table 13-12, the estimated average amount of time it takes to process one additional invoice is -Referring to Table 13-12, the estimated average amount of time it takes to process one additional invoice is

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TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output: TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output:    Note: 4.3946E-15 is 4.3946×10<sup>-15</sup>      -Referring to Table 13-12, the degrees of freedom for the t test on whether the number of invoices processed affects the amount of time are Note: 4.3946E-15 is 4.3946×10-15 TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output:    Note: 4.3946E-15 is 4.3946×10<sup>-15</sup>      -Referring to Table 13-12, the degrees of freedom for the t test on whether the number of invoices processed affects the amount of time are TABLE 13-12 The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of time (measured in hours) it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time in hours is recorded. Below is the regression output:    Note: 4.3946E-15 is 4.3946×10<sup>-15</sup>      -Referring to Table 13-12, the degrees of freedom for the t test on whether the number of invoices processed affects the amount of time are -Referring to Table 13-12, the degrees of freedom for the t test on whether the number of invoices processed affects the amount of time are

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TABLE 13-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: TABLE 13-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:    -Referring to Table 13-2, what is for these data?  -Referring to Table 13-2, what is for these data? TABLE 13-2 A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below:    -Referring to Table 13-2, what is for these data?

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TABLE 13-8 It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output from regressing GPA on ACT scores using a data set of 8 randomly chosen students from a Big-Ten university. TABLE 13-8 It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output from regressing GPA on ACT scores using a data set of 8 randomly chosen students from a Big-Ten university.    -Referring to Table 13-8, what are the decision and conclusion on testing whether there is any linear relationship at 1% level of significance between GPA and ACT scores? -Referring to Table 13-8, what are the decision and conclusion on testing whether there is any linear relationship at 1% level of significance between GPA and ACT scores?

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The coefficient of determination represents the ratio of SSR to SST.

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TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, the null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads is There is no linear relationship between revenue and the number of downloads. TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, the null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads is There is no linear relationship between revenue and the number of downloads. TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, the null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads is There is no linear relationship between revenue and the number of downloads. -Referring to Table 13-11, the null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads is "There is no linear relationship between revenue and the number of downloads."

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TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, what is the value of the test statistic for testing whether there is a linear relationship between revenue and the number of downloads? TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, what is the value of the test statistic for testing whether there is a linear relationship between revenue and the number of downloads? TABLE 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:        -Referring to Table 13-11, what is the value of the test statistic for testing whether there is a linear relationship between revenue and the number of downloads? -Referring to Table 13-11, what is the value of the test statistic for testing whether there is a linear relationship between revenue and the number of downloads?

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